2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)最新文献_第9页

Load-Balancing Techniques for 5G Millimeter-Wave Distributed Antenna System 5G毫米波分布式天线系统负载均衡技术

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9448953

Teppei Oyama, Takashi Seyama

引用次数: 4

Passive Beamforming Design for Reconfigurable Intelligent Surface-aided OFDM: A Fractional Programming Based Approach 可重构智能表面辅助OFDM的无源波束形成设计:一种基于分数规划的方法

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9449003

Keming Feng, Yijian Chen, Yu Han, Xiao Li, Shi Jin

{"title":"Passive Beamforming Design for Reconfigurable Intelligent Surface-aided OFDM: A Fractional Programming Based Approach","authors":"Keming Feng, Yijian Chen, Yu Han, Xiao Li, Shi Jin","doi":"10.1109/VTC2021-Spring51267.2021.9449003","DOIUrl":"https://doi.org/10.1109/VTC2021-Spring51267.2021.9449003","url":null,"abstract":"Reconfigurable intelligent surface (RIS) is a low-cost device envisioned to achieve substantial promotion in both spectrum and energy efficiency in the future wireless communication systems. In this paper, we investigate the downlink transmission of the RIS-enabled orthogonal frequency division multiplexing (OFDM) system, and propose a low-complexity passive beamforming optimization algorithm to maximize the achievable sum-rate over all subcarriers. The passive beam-forming optimization is a NP-hard problem due to the RIS-induced non-convex unit modulus constraints. We conquer this difficulty by exploiting a fractional programming (FP) based approach combined with an efficient manifold optimization (MO) method. With the proposed low-complexity passive beamforming optimization algorithms and water-filling power allocation, the achievable sum rate can then be maximized through alternating optimization (AO). Simulation results indicate that the proposed AO based algorithm performs well in achieving high average sum-rate with a fast convergence rate.","PeriodicalId":194840,"journal":{"name":"2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133956127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A 2D Non-Stationary Channel Model for Underwater Acoustic Communication Systems 水声通信系统的二维非平稳信道模型

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9448976

Xiuming Zhu, Chengxiang Wang, Ruofei Ma

引用次数: 6

Reliability Enhancement by PDCP Duplication and Combining for Next Generation Networks 下一代网络中PDCP复制与组合的可靠性增强

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9449079

A. M. Ahmed, A. Patel, Mohammed Zafar Ali Khan

{"title":"Reliability Enhancement by PDCP Duplication and Combining for Next Generation Networks","authors":"A. M. Ahmed, A. Patel, Mohammed Zafar Ali Khan","doi":"10.1109/VTC2021-Spring51267.2021.9449079","DOIUrl":"https://doi.org/10.1109/VTC2021-Spring51267.2021.9449079","url":null,"abstract":"User equipment (UE), in general, has access to multiple radio access technologies (RATS). Besides, secondary base-stations can also aid the UE’s communication. Thus data can reach the UE from the primary base-station via multiple secondary base-stations. Taking advantage of the benefits of using such multiple paths, we propose in this paper a cross-layer scheme that improves block error rate (BLER) and throughput. We propose data duplication and integration at the Packet Data Convergence Protocol (PDCP) sublayer of layer 2 for downlink operations of 4G LTE / 5G NR. At the PDCP of ENodeB (gnodeB), the PDCP protocol data unit (PDU) is duplicated and sent to the UE via various paths. All these PDUs have the same sequence number (SN). Data from various networks are aptly linked using the PDCP assigned SN at EnodeB to obtain a composite and improved version of the PDU at UE. Although the cross-layer technique involves new procedures when combining data at PDPCP, the average delay for a PDCP-based aggregation scheme is very small compared with the standalone scheme because of the significant improvement in the block error rate (BLER) provided by the scheme over the BLER of the traditional standalone system. Finally, the BLER improvement results in throughput enhancement.","PeriodicalId":194840,"journal":{"name":"2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113985899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Power Distribution Method of OFDM System with Hybrid Energy Supply under Fast Fading Channel 快速衰落信道下混合供能OFDM系统功率分配方法研究

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9448768

Yipeng Liu, Zhicheng Dong, Wei Xiao, E. Panayirci

引用次数: 0

Deep Reinforcement Learning for Edge Computing Resource Allocation in Blockchain Network Slicing Broker Framework 区块链网络切片代理框架中边缘计算资源分配的深度强化学习

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9449081

Yu Gong, Siyuan Sun, Yifei Wei, Mei Song

{"title":"Deep Reinforcement Learning for Edge Computing Resource Allocation in Blockchain Network Slicing Broker Framework","authors":"Yu Gong, Siyuan Sun, Yifei Wei, Mei Song","doi":"10.1109/VTC2021-Spring51267.2021.9449081","DOIUrl":"https://doi.org/10.1109/VTC2021-Spring51267.2021.9449081","url":null,"abstract":"With the constant development of 5G technology, such as softwareization and virtualization, the novel concept of network slicing has been appeared. Blockchain is a decentralized technology for managing transactions and data which can ensure the security of transaction. Recently, the classical mobile network introduces a new role such as network slice agent to provide slices for one or across multiple operators, providing services for users or vertical industries over a larger time and space range. In this paper, we propose the blockchain network slicing broker (BNSB), an intermediate broker, which receive resources request and response then allocation resources between Network Slice Tenants (NST) and then schedule physical resources from Infrastructure Provider (InP) through smart contracts. The topology information is obtained according to the Complex Network theory and the value of nodes is defined according to their importance. In addition, Deep Reinforcement Learning algorithms is used to explore the optimal policy under the condition of meeting the service Level Agreement (SLA).","PeriodicalId":194840,"journal":{"name":"2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","volume":"10 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114019966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Evaluation on a Drone Classification Method Using UWB Radar Image Recognition with Deep Learning 基于超宽带雷达图像识别和深度学习的无人机分类方法评价

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9448946

Daiki Kawaguchi, R. Nakamura, H. Hadama

引用次数: 3

Direction Aided Multipath Channel Estimation for Millimeter Wave Systems 毫米波系统的方向辅助多径信道估计

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9448770

Remun Koirala, B. Uguen, D. Dardari, H. Wymeersch, B. Denis

引用次数: 1

Channel Estimation Using Multi-stage Compressed Sensing for Millimeter Wave MIMO Systems 基于多级压缩感知的毫米波MIMO系统信道估计

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9448773

Baghdad Hadji, A. Aïssa-El-Bey, L. Fergani, M. Djeddou

{"title":"Channel Estimation Using Multi-stage Compressed Sensing for Millimeter Wave MIMO Systems","authors":"Baghdad Hadji, A. Aïssa-El-Bey, L. Fergani, M. Djeddou","doi":"10.1109/VTC2021-Spring51267.2021.9448773","DOIUrl":"https://doi.org/10.1109/VTC2021-Spring51267.2021.9448773","url":null,"abstract":"Millimeter-wave (mmWave) and multiple-input multiple-output (MIMO) combination technologies have at-tracted extensive attention from both academia and industry for meeting future communication challenges and requirements. As a viable option to deal with the trade-off between hardware complexity and system performance, hybrid analog/digital architectures are regarded as efficient mmWave MIMO transceivers. While acquiring channel state information (CSI) is a challenging task to design the optimal beamformers/combiners, especially in mmWave communications due to a lot of challenges. Fortunately, the sparse nature of the channel allows to leverage the compressed sensing (CS) tools and theories. However, the critical challenge to develop a CS-based formulation for estimating the mmWave channel is the codebook design (sensing matrices) and its pilot symbol numbers. In this paper, we proposed a multistage CS-based algorithm to estimate the channel explicitly using pilot and data symbols which enable increasing the number of measurements to enhance the estimation accuracy and maximize the spatial diversity by reducing the overlapping between training beams. Simulations confirmed that our proposed method has the best results compared to the existing methods based on codebook schemes.","PeriodicalId":194840,"journal":{"name":"2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116731792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Particle Swarm Optimization Algorithms for Altitude and Transmit Power Adjustments in UAV-Assisted Cellular Networks 无人机辅助蜂窝网络高度和发射功率调整的粒子群优化算法

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) Pub Date : 2021-04-01 DOI: 10.1109/VTC2021-Spring51267.2021.9448994

Shourya Shukla, Rahul Thakur, Swati Agarwal

引用次数: 2